Overview

Brought to you by YData

Dataset statistics

Number of variables11
Number of observations9000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory773.6 KiB
Average record size in memory88.0 B

Variable types

Numeric10
Categorical1

Alerts

X1 has unique values Unique
X2 has unique values Unique
X3 has unique values Unique
X4 has unique values Unique
X5 has unique values Unique
X6 has unique values Unique
X7 has unique values Unique
X8 has unique values Unique
X9 has unique values Unique
Y has unique values Unique

Reproduction

Analysis started2025-03-29 02:22:59.915908
Analysis finished2025-03-29 02:23:03.861929
Duration3.95 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

X1
Real number (ℝ)

Unique 

Distinct9000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.069296
Minimum10.000557
Maximum29.999817
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size70.4 KiB
2025-03-29T13:23:03.896523image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum10.000557
5-th percentile10.997532
Q115.119925
median20.042837
Q325.1303
95-th percentile29.005807
Maximum29.999817
Range19.99926
Interquartile range (IQR)10.010375

Descriptive statistics

Standard deviation5.7921688
Coefficient of variation (CV)0.28860846
Kurtosis-1.1952724
Mean20.069296
Median Absolute Deviation (MAD)4.9910965
Skewness-0.0060009609
Sum180623.67
Variance33.549219
MonotonicityNot monotonic
2025-03-29T13:23:03.943010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20.23643249 1
 
< 0.1%
29.91607596 1
 
< 0.1%
22.88992327 1
 
< 0.1%
25.97912541 1
 
< 0.1%
25.68066846 1
 
< 0.1%
19.61739799 1
 
< 0.1%
16.90689399 1
 
< 0.1%
10.46536899 1
 
< 0.1%
28.15373761 1
 
< 0.1%
12.09703985 1
 
< 0.1%
Other values (8990) 8990
99.9%
ValueCountFrequency (%)
10.00055715 1
< 0.1%
10.00350518 1
< 0.1%
10.00494377 1
< 0.1%
10.00924098 1
< 0.1%
10.01204476 1
< 0.1%
10.01261746 1
< 0.1%
10.01581231 1
< 0.1%
10.01774751 1
< 0.1%
10.01840275 1
< 0.1%
10.02100561 1
< 0.1%
ValueCountFrequency (%)
29.99981691 1
< 0.1%
29.99711605 1
< 0.1%
29.99651189 1
< 0.1%
29.99649027 1
< 0.1%
29.99259181 1
< 0.1%
29.9907791 1
< 0.1%
29.99006796 1
< 0.1%
29.98921586 1
< 0.1%
29.98684522 1
< 0.1%
29.98577473 1
< 0.1%

X2
Real number (ℝ)

Unique 

Distinct9000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.050879
Minimum20.000796
Maximum69.996616
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size70.4 KiB
2025-03-29T13:23:03.984720image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum20.000796
5-th percentile22.375332
Q132.314342
median45.184259
Q357.836858
95-th percentile67.302802
Maximum69.996616
Range49.99582
Interquartile range (IQR)25.522516

Descriptive statistics

Standard deviation14.461923
Coefficient of variation (CV)0.32101312
Kurtosis-1.2141992
Mean45.050879
Median Absolute Deviation (MAD)12.739448
Skewness-0.017837104
Sum405457.92
Variance209.14722
MonotonicityNot monotonic
2025-03-29T13:23:04.027537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
67.52318482 1
 
< 0.1%
26.21880896 1
 
< 0.1%
32.51491787 1
 
< 0.1%
36.390955 1
 
< 0.1%
35.32688152 1
 
< 0.1%
62.88235397 1
 
< 0.1%
22.6309286 1
 
< 0.1%
42.16191015 1
 
< 0.1%
38.73830953 1
 
< 0.1%
60.58174239 1
 
< 0.1%
Other values (8990) 8990
99.9%
ValueCountFrequency (%)
20.00079581 1
< 0.1%
20.00129219 1
< 0.1%
20.00562533 1
< 0.1%
20.0063135 1
< 0.1%
20.01268441 1
< 0.1%
20.02164425 1
< 0.1%
20.02538498 1
< 0.1%
20.02841562 1
< 0.1%
20.02951989 1
< 0.1%
20.03057508 1
< 0.1%
ValueCountFrequency (%)
69.99661551 1
< 0.1%
69.98548042 1
< 0.1%
69.98001538 1
< 0.1%
69.97138907 1
< 0.1%
69.97054251 1
< 0.1%
69.97046204 1
< 0.1%
69.96526405 1
< 0.1%
69.96306376 1
< 0.1%
69.95865755 1
< 0.1%
69.95826844 1
< 0.1%

X3
Real number (ℝ)

Unique 

Distinct9000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.038058
Minimum30.000634
Maximum69.993742
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size70.4 KiB
2025-03-29T13:23:04.067778image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum30.000634
5-th percentile32.006929
Q139.976964
median49.953152
Q360.081216
95-th percentile68.068052
Maximum69.993742
Range39.993109
Interquartile range (IQR)20.104251

Descriptive statistics

Standard deviation11.603689
Coefficient of variation (CV)0.23189726
Kurtosis-1.2132785
Mean50.038058
Median Absolute Deviation (MAD)10.046959
Skewness0.0046882506
Sum450342.52
Variance134.64559
MonotonicityNot monotonic
2025-03-29T13:23:04.108470image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.76638451 1
 
< 0.1%
67.87101166 1
 
< 0.1%
64.08997255 1
 
< 0.1%
52.89922001 1
 
< 0.1%
44.18128026 1
 
< 0.1%
63.40495886 1
 
< 0.1%
51.68771803 1
 
< 0.1%
61.57721641 1
 
< 0.1%
56.38429924 1
 
< 0.1%
52.22633262 1
 
< 0.1%
Other values (8990) 8990
99.9%
ValueCountFrequency (%)
30.0006338 1
< 0.1%
30.00164885 1
< 0.1%
30.00622871 1
< 0.1%
30.00630816 1
< 0.1%
30.0089792 1
< 0.1%
30.01315347 1
< 0.1%
30.01728784 1
< 0.1%
30.02905342 1
< 0.1%
30.030276 1
< 0.1%
30.0417773 1
< 0.1%
ValueCountFrequency (%)
69.99374232 1
< 0.1%
69.99368379 1
< 0.1%
69.9892171 1
< 0.1%
69.98158495 1
< 0.1%
69.98119704 1
< 0.1%
69.97547265 1
< 0.1%
69.97286038 1
< 0.1%
69.9702557 1
< 0.1%
69.96977662 1
< 0.1%
69.95828798 1
< 0.1%

X4
Real number (ℝ)

Unique 

Distinct9000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.96845
Minimum40.000622
Maximum69.993734
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size70.4 KiB
2025-03-29T13:23:04.150202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum40.000622
5-th percentile41.595475
Q147.541766
median54.883777
Q362.611018
95-th percentile68.445553
Maximum69.993734
Range29.993112
Interquartile range (IQR)15.069252

Descriptive statistics

Standard deviation8.6557612
Coefficient of variation (CV)0.1574678
Kurtosis-1.2100837
Mean54.96845
Median Absolute Deviation (MAD)7.5363354
Skewness0.0052662863
Sum494716.05
Variance74.922201
MonotonicityNot monotonic
2025-03-29T13:23:04.191204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
68.45948341 1
 
< 0.1%
45.4212676 1
 
< 0.1%
46.97249384 1
 
< 0.1%
51.87075394 1
 
< 0.1%
57.53424954 1
 
< 0.1%
64.53566224 1
 
< 0.1%
66.80114819 1
 
< 0.1%
69.89111765 1
 
< 0.1%
45.22655419 1
 
< 0.1%
42.4896853 1
 
< 0.1%
Other values (8990) 8990
99.9%
ValueCountFrequency (%)
40.00062228 1
< 0.1%
40.0019107 1
< 0.1%
40.00764757 1
< 0.1%
40.02227877 1
< 0.1%
40.02414304 1
< 0.1%
40.0256323 1
< 0.1%
40.0401202 1
< 0.1%
40.04201062 1
< 0.1%
40.04880617 1
< 0.1%
40.05119793 1
< 0.1%
ValueCountFrequency (%)
69.99373431 1
< 0.1%
69.99162318 1
< 0.1%
69.98437959 1
< 0.1%
69.96110978 1
< 0.1%
69.95882201 1
< 0.1%
69.95779612 1
< 0.1%
69.94901468 1
< 0.1%
69.94295472 1
< 0.1%
69.94164129 1
< 0.1%
69.93788764 1
< 0.1%

X5
Real number (ℝ)

Unique 

Distinct9000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.716805
Minimum50.026769
Maximum129.98902
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size70.4 KiB
2025-03-29T13:23:04.231849image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum50.026769
5-th percentile53.955504
Q169.78216
median89.430978
Q3109.86155
95-th percentile125.91702
Maximum129.98902
Range79.96225
Interquartile range (IQR)40.079386

Descriptive statistics

Standard deviation23.161377
Coefficient of variation (CV)0.25816096
Kurtosis-1.2061833
Mean89.716805
Median Absolute Deviation (MAD)20.0576
Skewness0.020178869
Sum807451.25
Variance536.44938
MonotonicityNot monotonic
2025-03-29T13:23:04.358980image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74.94651616 1
 
< 0.1%
106.3075469 1
 
< 0.1%
79.60281479 1
 
< 0.1%
129.8970435 1
 
< 0.1%
76.77722567 1
 
< 0.1%
66.84766358 1
 
< 0.1%
104.5982908 1
 
< 0.1%
122.5033185 1
 
< 0.1%
128.6479346 1
 
< 0.1%
59.67728288 1
 
< 0.1%
Other values (8990) 8990
99.9%
ValueCountFrequency (%)
50.02676926 1
< 0.1%
50.02795747 1
< 0.1%
50.029381 1
< 0.1%
50.04227163 1
< 0.1%
50.04786432 1
< 0.1%
50.04999459 1
< 0.1%
50.05574643 1
< 0.1%
50.06283582 1
< 0.1%
50.0706656 1
< 0.1%
50.08238612 1
< 0.1%
ValueCountFrequency (%)
129.9890192 1
< 0.1%
129.9805874 1
< 0.1%
129.9780417 1
< 0.1%
129.9779156 1
< 0.1%
129.9762731 1
< 0.1%
129.970563 1
< 0.1%
129.9668245 1
< 0.1%
129.9624443 1
< 0.1%
129.9619806 1
< 0.1%
129.9612567 1
< 0.1%

X6
Real number (ℝ)

Unique 

Distinct9000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.948054
Minimum60.002514
Maximum129.98706
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size70.4 KiB
2025-03-29T13:23:04.400657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum60.002514
5-th percentile63.434111
Q177.455233
median94.80085
Q3112.50132
95-th percentile126.47567
Maximum129.98706
Range69.984549
Interquartile range (IQR)35.046085

Descriptive statistics

Standard deviation20.261797
Coefficient of variation (CV)0.21339876
Kurtosis-1.2036266
Mean94.948054
Median Absolute Deviation (MAD)17.531613
Skewness0.0031647686
Sum854532.48
Variance410.54041
MonotonicityNot monotonic
2025-03-29T13:23:04.441424image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
89.63285143 1
 
< 0.1%
101.7345079 1
 
< 0.1%
109.5637104 1
 
< 0.1%
100.7342777 1
 
< 0.1%
76.66700263 1
 
< 0.1%
91.71512784 1
 
< 0.1%
66.20968499 1
 
< 0.1%
114.5721017 1
 
< 0.1%
80.91861649 1
 
< 0.1%
102.1261348 1
 
< 0.1%
Other values (8990) 8990
99.9%
ValueCountFrequency (%)
60.00251363 1
< 0.1%
60.02045358 1
< 0.1%
60.02191787 1
< 0.1%
60.02524251 1
< 0.1%
60.02637457 1
< 0.1%
60.03584218 1
< 0.1%
60.04912823 1
< 0.1%
60.0514991 1
< 0.1%
60.07071657 1
< 0.1%
60.07219469 1
< 0.1%
ValueCountFrequency (%)
129.9870625 1
< 0.1%
129.9844228 1
< 0.1%
129.9659346 1
< 0.1%
129.964648 1
< 0.1%
129.9439523 1
< 0.1%
129.9247053 1
< 0.1%
129.9062177 1
< 0.1%
129.8812251 1
< 0.1%
129.8651132 1
< 0.1%
129.8592819 1
< 0.1%

X7
Real number (ℝ)

Unique 

Distinct9000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.028888
Minimum70.000821
Maximum79.997789
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size70.4 KiB
2025-03-29T13:23:04.482670image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum70.000821
5-th percentile70.558887
Q172.552686
median75.031206
Q377.521159
95-th percentile79.513419
Maximum79.997789
Range9.9969683
Interquartile range (IQR)4.9684723

Descriptive statistics

Standard deviation2.8667808
Coefficient of variation (CV)0.038209027
Kurtosis-1.2039104
Mean75.028888
Median Absolute Deviation (MAD)2.4822311
Skewness-0.0035488736
Sum675260
Variance8.2184322
MonotonicityNot monotonic
2025-03-29T13:23:04.523322image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
78.27702594 1
 
< 0.1%
73.74164814 1
 
< 0.1%
73.10091526 1
 
< 0.1%
72.40136134 1
 
< 0.1%
77.81865155 1
 
< 0.1%
76.71956443 1
 
< 0.1%
70.61285387 1
 
< 0.1%
74.35245448 1
 
< 0.1%
76.59472427 1
 
< 0.1%
76.28628498 1
 
< 0.1%
Other values (8990) 8990
99.9%
ValueCountFrequency (%)
70.00082079 1
< 0.1%
70.00096041 1
< 0.1%
70.00321623 1
< 0.1%
70.0037829 1
< 0.1%
70.00401948 1
< 0.1%
70.00577014 1
< 0.1%
70.00604784 1
< 0.1%
70.00612668 1
< 0.1%
70.00629782 1
< 0.1%
70.00760648 1
< 0.1%
ValueCountFrequency (%)
79.99778907 1
< 0.1%
79.9952182 1
< 0.1%
79.994166 1
< 0.1%
79.99284263 1
< 0.1%
79.99260124 1
< 0.1%
79.99241096 1
< 0.1%
79.99025882 1
< 0.1%
79.98652629 1
< 0.1%
79.98562592 1
< 0.1%
79.9842299 1
< 0.1%

X8
Real number (ℝ)

Unique 

Distinct9000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean124.98559
Minimum80.001021
Maximum169.98768
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size70.4 KiB
2025-03-29T13:23:04.564383image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum80.001021
5-th percentile84.279543
Q1102.31459
median124.80178
Q3147.66182
95-th percentile165.32441
Maximum169.98768
Range89.986657
Interquartile range (IQR)45.347228

Descriptive statistics

Standard deviation25.992992
Coefficient of variation (CV)0.20796791
Kurtosis-1.1947549
Mean124.98559
Median Absolute Deviation (MAD)22.643192
Skewness0.0041437059
Sum1124870.3
Variance675.63566
MonotonicityNot monotonic
2025-03-29T13:23:04.604301image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
116.8279223 1
 
< 0.1%
151.1982609 1
 
< 0.1%
115.7730073 1
 
< 0.1%
158.7019445 1
 
< 0.1%
106.3921367 1
 
< 0.1%
128.1197229 1
 
< 0.1%
114.4770853 1
 
< 0.1%
133.7526163 1
 
< 0.1%
88.41734248 1
 
< 0.1%
160.127316 1
 
< 0.1%
Other values (8990) 8990
99.9%
ValueCountFrequency (%)
80.00102052 1
< 0.1%
80.02847661 1
< 0.1%
80.02883846 1
< 0.1%
80.03173725 1
< 0.1%
80.04200683 1
< 0.1%
80.05247317 1
< 0.1%
80.06789151 1
< 0.1%
80.10367333 1
< 0.1%
80.1102385 1
< 0.1%
80.11137048 1
< 0.1%
ValueCountFrequency (%)
169.9876775 1
< 0.1%
169.9868997 1
< 0.1%
169.9686484 1
< 0.1%
169.9469974 1
< 0.1%
169.9421923 1
< 0.1%
169.9335945 1
< 0.1%
169.9016989 1
< 0.1%
169.8951404 1
< 0.1%
169.8892101 1
< 0.1%
169.878105 1
< 0.1%

X9
Real number (ℝ)

Unique 

Distinct9000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean119.99949
Minimum90.005333
Maximum149.99406
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size70.4 KiB
2025-03-29T13:23:04.642114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum90.005333
5-th percentile92.944334
Q1105.17878
median120.28353
Q3134.76644
95-th percentile147.01724
Maximum149.99406
Range59.988723
Interquartile range (IQR)29.587663

Descriptive statistics

Standard deviation17.284227
Coefficient of variation (CV)0.14403583
Kurtosis-1.186838
Mean119.99949
Median Absolute Deviation (MAD)14.828068
Skewness-0.0049328637
Sum1079995.4
Variance298.74451
MonotonicityNot monotonic
2025-03-29T13:23:04.682783image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
122.9756213 1
 
< 0.1%
145.7106236 1
 
< 0.1%
95.84707157 1
 
< 0.1%
94.4518675 1
 
< 0.1%
125.6881356 1
 
< 0.1%
116.6330226 1
 
< 0.1%
127.4598413 1
 
< 0.1%
141.0837944 1
 
< 0.1%
141.8471781 1
 
< 0.1%
121.2640984 1
 
< 0.1%
Other values (8990) 8990
99.9%
ValueCountFrequency (%)
90.00533304 1
< 0.1%
90.00950016 1
< 0.1%
90.01396111 1
< 0.1%
90.04945966 1
< 0.1%
90.05118797 1
< 0.1%
90.05127489 1
< 0.1%
90.05219425 1
< 0.1%
90.05330165 1
< 0.1%
90.0557836 1
< 0.1%
90.06139217 1
< 0.1%
ValueCountFrequency (%)
149.9940556 1
< 0.1%
149.9851266 1
< 0.1%
149.9703775 1
< 0.1%
149.9655572 1
< 0.1%
149.9588698 1
< 0.1%
149.9540492 1
< 0.1%
149.9453825 1
< 0.1%
149.9304614 1
< 0.1%
149.9243454 1
< 0.1%
149.9240142 1
< 0.1%

X10
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size70.4 KiB
AED
1556 
OIF
1553 
QWE
1524 
ACV
1486 
DAF
1462 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters27000
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDEB
2nd rowAED
3rd rowDAF
4th rowACV
5th rowDAF

Common Values

ValueCountFrequency (%)
AED 1556
17.3%
OIF 1553
17.3%
QWE 1524
16.9%
ACV 1486
16.5%
DAF 1462
16.2%
DEB 1419
15.8%

Length

2025-03-29T13:23:04.717457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-29T13:23:04.741838image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
aed 1556
17.3%
oif 1553
17.3%
qwe 1524
16.9%
acv 1486
16.5%
daf 1462
16.2%
deb 1419
15.8%

Most occurring characters

ValueCountFrequency (%)
A 4504
16.7%
E 4499
16.7%
D 4437
16.4%
F 3015
11.2%
O 1553
 
5.8%
I 1553
 
5.8%
Q 1524
 
5.6%
W 1524
 
5.6%
C 1486
 
5.5%
V 1486
 
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 27000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 4504
16.7%
E 4499
16.7%
D 4437
16.4%
F 3015
11.2%
O 1553
 
5.8%
I 1553
 
5.8%
Q 1524
 
5.6%
W 1524
 
5.6%
C 1486
 
5.5%
V 1486
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 27000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 4504
16.7%
E 4499
16.7%
D 4437
16.4%
F 3015
11.2%
O 1553
 
5.8%
I 1553
 
5.8%
Q 1524
 
5.6%
W 1524
 
5.6%
C 1486
 
5.5%
V 1486
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 27000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 4504
16.7%
E 4499
16.7%
D 4437
16.4%
F 3015
11.2%
O 1553
 
5.8%
I 1553
 
5.8%
Q 1524
 
5.6%
W 1524
 
5.6%
C 1486
 
5.5%
V 1486
 
5.5%

Y
Real number (ℝ)

Unique 

Distinct9000
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean870.37768
Minimum627.11857
Maximum1134.2196
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size70.4 KiB
2025-03-29T13:23:04.781686image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum627.11857
5-th percentile726.03989
Q1815.99535
median875.60979
Q3927.16151
95-th percentile997.77741
Maximum1134.2196
Range507.101
Interquartile range (IQR)111.16616

Descriptive statistics

Standard deviation81.251214
Coefficient of variation (CV)0.093351674
Kurtosis-0.2947511
Mean870.37768
Median Absolute Deviation (MAD)55.260894
Skewness-0.18719128
Sum7833399.1
Variance6601.7597
MonotonicityNot monotonic
2025-03-29T13:23:04.821090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
842.5474409 1
 
< 0.1%
942.7254832 1
 
< 0.1%
835.0612006 1
 
< 0.1%
891.7066279 1
 
< 0.1%
910.9454854 1
 
< 0.1%
912.6163834 1
 
< 0.1%
702.5139842 1
 
< 0.1%
826.5958349 1
 
< 0.1%
943.3007461 1
 
< 0.1%
890.4591131 1
 
< 0.1%
Other values (8990) 8990
99.9%
ValueCountFrequency (%)
627.1185668 1
< 0.1%
637.4721456 1
< 0.1%
638.4079908 1
< 0.1%
642.475295 1
< 0.1%
644.4749747 1
< 0.1%
646.9389362 1
< 0.1%
647.3903416 1
< 0.1%
648.9361114 1
< 0.1%
649.2712284 1
< 0.1%
650.7007299 1
< 0.1%
ValueCountFrequency (%)
1134.219571 1
< 0.1%
1114.958099 1
< 0.1%
1106.978749 1
< 0.1%
1106.258432 1
< 0.1%
1103.103895 1
< 0.1%
1102.272968 1
< 0.1%
1099.716992 1
< 0.1%
1095.922193 1
< 0.1%
1089.189774 1
< 0.1%
1087.637309 1
< 0.1%

Interactions

2025-03-29T13:23:03.450446image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.143942image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.592319image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.909855image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.344501image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.699171image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.061640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.398261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.716573image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.120944image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.483372image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.213286image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.625957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.947539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.378949image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.736082image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.096759image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.431737image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.750105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.155969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.513389image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.260762image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.657467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.979568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.410434image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.769326image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.129778image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.461360image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.780799image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.187484image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.546226image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.304569image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.690035image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.106744image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.462466image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.804698image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.163572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.494918image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.812596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.221073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.577846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.364866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.721827image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.140642image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.501821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.841890image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.197510image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.526135image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.934492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.254422image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.611214image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.418599image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.754669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.175974image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.536921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.894374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.230699image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.560144image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.967329image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.287668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.643252image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.454672image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.787238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.211209image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.571075image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.928856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.266476image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.591807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.999238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.322596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.675470image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.489050image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.818601image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.244146image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.602541image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.962036image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.298345image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.623701image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.029161image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.354467image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.721318image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.522868image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.850212image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.277916image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.634052image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.995472image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.331154image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.653217image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.058742image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.386308image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.753663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.558729image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:00.881365image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.311096image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:01.666724image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.028512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.364764image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:02.686338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.089751image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-29T13:23:03.417840image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-03-29T13:23:04.853482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
X1X10X2X3X4X5X6X7X8X9Y
X11.0000.000-0.0080.015-0.0080.0010.0090.010-0.003-0.0050.045
X100.0001.0000.0000.0170.0000.0000.0000.0090.0000.0000.398
X2-0.0080.0001.000-0.0200.0160.029-0.0070.001-0.041-0.0000.058
X30.0150.017-0.0201.0000.0150.004-0.0020.0030.017-0.0160.106
X4-0.0080.0000.0160.0151.0000.0080.0110.014-0.0110.003-0.059
X50.0010.0000.0290.0040.0081.0000.015-0.0010.0110.004-0.075
X60.0090.000-0.007-0.0020.0110.0151.0000.006-0.0100.003-0.103
X70.0100.0090.0010.0030.014-0.0010.0061.0000.0230.0030.360
X8-0.0030.000-0.0410.017-0.0110.011-0.0100.0231.000-0.0160.351
X9-0.0050.000-0.000-0.0160.0030.0040.0030.003-0.0161.0000.351
Y0.0450.3980.0580.106-0.059-0.075-0.1030.3600.3510.3511.000

Missing values

2025-03-29T13:23:03.801780image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-29T13:23:03.836355image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

X1X2X3X4X5X6X7X8X9X10Y
020.23643267.52318535.76638568.45948374.94651689.63285178.277026116.827922122.975621DEB842.547441
110.55118257.67565551.52573349.891951113.07429681.22363874.53497992.063753114.186779AED842.138909
214.06910533.11566760.01458748.41226388.815278128.65160479.616572145.231095122.473611DAF820.804741
315.53782428.03260068.79701755.48205859.269249103.64428377.766831135.170297145.037862ACV962.565837
410.79185846.42946348.37343541.870487101.306253119.68429975.929410103.408770140.392891DAF758.052022
520.18991845.54444460.12120844.437661115.570138107.83008377.87096997.245463138.141850ACV899.836703
613.82647924.07763164.20907965.838505120.12296893.03368072.74048480.638265128.743254AED831.678380
724.39818861.77846141.27511346.456545101.146510116.35383879.63670993.547235118.932743ACV883.064019
827.89431741.13584553.58008240.734720103.876791124.33620378.268253159.696824129.621323DAF841.863027
914.91104558.42585038.46699064.93824555.017434117.78414771.645073113.763230109.004290AED809.507523
X1X2X3X4X5X6X7X8X9X10Y
899019.64957543.01210855.41165267.76701586.600357111.23112874.028474164.756326116.637805DAF774.073995
899114.06516222.89182660.92004651.08736180.218422121.54324276.891083114.879732139.591223QWE959.770678
899220.03947542.62413561.24922656.151374116.63728498.71708771.101104111.760885105.368371OIF840.381481
899326.51012838.90670239.93145064.02638183.02863168.94898572.858872156.90012698.554258DAF743.720435
899414.51510664.96242537.39271454.829748128.746428119.88884977.716498147.140576133.040182QWE975.072748
899523.83403060.87035439.40805460.09140357.54762468.12183773.051684143.508784145.519836DAF819.612981
899620.48513727.69810651.71331366.75491879.80097565.51960172.54192398.308787113.326350OIF846.890940
899724.22101325.55079349.72393965.29994382.698026101.45241076.711958149.865618100.804168DEB827.582394
899823.56947528.57924259.74654841.91871160.23461384.03299378.04555284.804789130.333127QWE970.751368
899922.00641947.04826550.32476855.498333101.35721079.96386071.807592164.727897131.694479ACV918.001315